Construction of Cross-Border e-Commerce Financial Risk Analysis System Based on Support Vector Machine

Abstract

The rapid changes in the economic situation and the complex market environment make the cross-border e-commerce industry, as an important part of the market economy, face many challenges and risks in the development process. The particularity of its transaction and the imperfect tax mechanism have virtually increased the financial management risk. The research constructs the financial risk analysis model with the help of the support vector machine (SVM) and fuzzy theory. Through algorithm test and empirical research, it is found that the average accuracy of the optimized SVM on the selected data set is more than 90%, and after parameter optimization, the change of model fitness tends to be stable with the increase of iteration times, which greatly improves the search ability of sample data, and the accuracy of financial data classification with high risk is 46.8%. In the empirical research, the model established by fuzzy SVM can effectively eliminate the irrelevant index data, and the prediction accuracy of investment risk and operation risk has reached 80% or more. In the prediction of financing risk and tax risk, its accuracy has been improved by 12.4% compared to that before use.

RETRACTED ARTICLE: A Multilevel Fuzzy Evaluation of Cross-Border E-Commerce Profitability Model

“…CBEC refers to companies which do international commerce, use online platforms, carry out agreements or cooperative activities, accept payments through online bank transfers and other channels, and depend on cross-border logistics to complete product transit [10,11]. CBEC is divided into four modes, namely, B2B, B2C, B2G and C2C [12,13].…”

How Do Information Sources Influence the Purchases of Tourism, Culture, and Entertainment? An Analysis of China Family Panel Studies Data

“…The sources of information need to be enriched for all people. Particularly, governments should continue to expand rural informatization, give more emphasis to the critical role of the Internet and other new information channels (H. M. Li & Zhang, 2019), improve the weaker state of rural network infrastructure, and redress the situation of ''information island'' in rural areas (Wang et al, 2022). Also, local governments and tourism and culture agencies should reinforce contact with information management departments and standardize information transmission quality through different sources.…”

Design and Application of Global Energy Trade Cross Border E-commerce Optimization Model

“…The second generation of EMO methods is based on the original genetic algorithms and uses an external population-based approach to maintain elite individuals [20] . For example, genetic algorithms based on Pareto optimal solutions (SPEA, SPEA2), external population-based evolutionary strategies (PAES) and the most classical NSGA-II [21] . For the optimization problem of multi-modal joint transportation networks, a path-based optimization algorithm is proposed and solved by using the decomposition search algorithm, which proves that the proposed method can better solve the 150-node nontrivial problems and is better than some existing approximate solutions.…”